• Title/Summary/Keyword: spatial network

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Recognition of Flat Type Signboard using Deep Learning (딥러닝을 이용한 판류형 간판의 인식)

  • Kwon, Sang Il;Kim, Eui Myoung
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.4
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    • pp.219-231
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    • 2019
  • The specifications of signboards are set for each type of signboards, but the shape and size of the signboard actually installed are not uniform. In addition, because the colors of the signboard are not defined, so various colors are applied to the signboard. Methods for recognizing signboards can be thought of as similar methods of recognizing road signs and license plates, but due to the nature of the signboards, there are limitations in that the signboards can not be recognized in a way similar to road signs and license plates. In this study, we proposed a methodology for recognizing plate-type signboards, which are the main targets of illegal and old signboards, and automatically extracting areas of signboards, using the deep learning-based Faster R-CNN algorithm. The process of recognizing flat type signboards through signboard images captured by using smartphone cameras is divided into two sequences. First, the type of signboard was recognized using deep learning to recognize flat type signboards in various types of signboard images, and the result showed an accuracy of about 71%. Next, when the boundary recognition algorithm for the signboards was applied to recognize the boundary area of the flat type signboard, the boundary of flat type signboard was recognized with an accuracy of 85%.

A Study on the Land-Use Related Assessment Factors in Korean Environmental Impact Assessment (환경영향평가 토지환경 분야의 토지이용 평가항목 고찰 연구)

  • Park, Sang-Jin;Lee, Dong Kun;Jeong, Seulgi
    • Journal of Environmental Impact Assessment
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    • v.30 no.5
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    • pp.297-304
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    • 2021
  • The environmental impact assessment(EIA) project in Korea has undergone changes and revisions in various evaluation items for about 30 years after the introduction of the Environmental Conservation Act (1997). However, despite the importance of land use evaluation items under the current EIA Act, there are insufficient studies to consider. Therefore, this study focused on the land-use evaluation items based on the EIA guidelines, reviewed 90 of the evaluation documents and consultation documents, and tried to suggest implications and supplementary points forthe domestic EIA land-use evaluation items. As a result, the paradigm was changing from land efficiency centered on development in the past to land efficiency centered on the natural environment and resource conservation. However, in spite of the manual for fitting the paradigm change, opinions on the conservation of the natural environment are still being drawn in the consultation document, so it needs improvement. Two improvements in the impact assessment process suggested in this study are the establishment of standardized spatial data and a quantitative impact and reduction method evaluation tool based on it. In particular, there is a need for a plan evaluation tool for land use arrangement and distribution that can solve the needs of minimizing damage to the natural environment and securing green space and a green network.

Does sports intelligence, the ability to read the game, exist? A systematic review of the relationship between sports performance and cognitive functions (게임을 읽는 머리, 스포츠 지능이 존재하는가? 스포츠 수행과 관련된 인지기능에 관한 문헌고찰)

  • Yongtawee, Atcharat;Park, Jin-Han;Woo, Min-Jung
    • Journal of the Korea Convergence Society
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    • v.12 no.3
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    • pp.325-339
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    • 2021
  • The purpose of the study is to examine sports-related cognitive functions through a systematic review and to suggest effective instruments to measure the cognitive functions. The present study was conducted based on the systematic review and meta-analysis protocol-the PRISMA. Of 429 articles searched through keywords from 2008 to 2020, 45 articles that met the selection criteria were analyzed. It was revealed that athletes had better cognitive functions than non-athletes, that the higher the sports expertise was, the higher the cognitive functions, and that there were differences in cognitive functions according to the sport types. The primary cognitive functions related to sports performance summarized as executive functions (inhibition ability, cognitive flexibility), information processing speed, spatial ability, and attention. As tasks for measuring each cognitive function, a stop signal task for inhibition ability, a design flexibility task for cognitive flexibility, a simple and choice reaction time test for information processing, a mental rotation task for spatial ability, and an attention network test for attention are appropriate.

MLP-based 3D Geotechnical Layer Mapping Using Borehole Database in Seoul, South Korea (MLP 기반의 서울시 3차원 지반공간모델링 연구)

  • Ji, Yoonsoo;Kim, Han-Saem;Lee, Moon-Gyo;Cho, Hyung-Ik;Sun, Chang-Guk
    • Journal of the Korean Geotechnical Society
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    • v.37 no.5
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    • pp.47-63
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    • 2021
  • Recently, the demand for three-dimensional (3D) underground maps from the perspective of digital twins and the demand for linkage utilization are increasing. However, the vastness of national geotechnical survey data and the uncertainty in applying geostatistical techniques pose challenges in modeling underground regional geotechnical characteristics. In this study, an optimal learning model based on multi-layer perceptron (MLP) was constructed for 3D subsurface lithological and geotechnical classification in Seoul, South Korea. First, the geotechnical layer and 3D spatial coordinates of each borehole dataset in the Seoul area were constructed as a geotechnical database according to a standardized format, and data pre-processing such as correction and normalization of missing values for machine learning was performed. An optimal fitting model was designed through hyperparameter optimization of the MLP model and model performance evaluation, such as precision and accuracy tests. Then, a 3D grid network locally assigning geotechnical layer classification was constructed by applying an MLP-based bet-fitting model for each unit lattice. The constructed 3D geotechnical layer map was evaluated by comparing the results of a geostatistical interpolation technique and the topsoil properties of the geological map.

A Road Environment Analysis for the Introduction of Connected and Automated Driving-based Mobility Services from an Operational Design Domain Perspective (자율주행기반 모빌리티 서비스 도입을 위한 운행설계영역 관점의 도로환경 분석)

  • Bo-Ram, WOO;Ah-Reum, KIM;Yong-Jun, AHN;Se-Hyun, TAK
    • Journal of the Korean Association of Geographic Information Studies
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    • v.25 no.4
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    • pp.107-118
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    • 2022
  • As connected and automated driving(CAD) technology is entering its commercialization stage, service platforms providing CAD-based mobility services have increased these days. However, CAD-baded mobility services with these platforms need more consideration for the demand for mobility services when determining target areas for CAD-based mobility services because current CAB-based mobility design focus on driving performance and driving stability. For a more efficient design of CAD-based mobility services, we analyzed the applicability for the introduction of CAD-based mobility services in terms of driving difficulty of CAD and demand patterns of current non-CAD based-mobility services, e.g., taxi, demand-responsive transit(DRT), and special transportation systems(STS). In addition, for the spatial analysis of the applicability of the CAD-based mobility service, we propose the Index for Autonomous Driving Applicability (IADA) and analyze the characteristics of the spatial distribution of IADA from the network perspective. The analysis results show that the applicability of CAD-based mobility services depends more on the demand patterns than the driving difficulty of CAV. In particular, the results show that the concentration pattern of demand in a specific road link is more important than the size of demand. As a result, STS service shows higher applicability compared to other mobility services, even though the size of demand for this mobility service is relatively small.

Development of a Stochastic Precipitation Generation Model for Generating Multi-site Daily Precipitation (다지점 일강수 모의를 위한 추계학적 강수모의모형의 구축)

  • Jeong, Dae-Il
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.5B
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    • pp.397-408
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    • 2009
  • In this study, a stochastic precipitation generation framework for simultaneous simulation of daily precipitation at multiple sites is presented. The precipitation occurrence at individual sites is generated using hybrid-order Markov chain model which allows higher-order dependence for dry sequences. The precipitation amounts are reproduced using Anscombe residuals and gamma distributions. Multisite spatial correlations in the precipitation occurrence and amount series are represented with spatially correlated random numbers. The proposed model is applied for a network of 17 locations in the middle of Korean peninsular. Evaluation statistics are reported by generating 50 realizations of the precipitation of length equal to the observed record. The analysis of results show that the model reproduces wet day number, wet and dry day spell, and mean and standard deviation of wet day amount fairly well. However, mean values of 50 realizations of generated precipitation series yield around 23% Root Mean Square Errors (RMSE) of the average value of observed maximum numbers of consecutive wet and dry days and 17% RMSE of the average value of observed annual maximum precipitations for return periods of 100 and 200 years. The provided model also reproduces spatial correlations in observed precipitation occurrence and amount series accurately.

An Implementation of Dynamic Gesture Recognizer Based on WPS and Data Glove (WPS와 장갑 장치 기반의 동적 제스처 인식기의 구현)

  • Kim, Jung-Hyun;Roh, Yong-Wan;Hong, Kwang-Seok
    • The KIPS Transactions:PartB
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    • v.13B no.5 s.108
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    • pp.561-568
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    • 2006
  • WPS(Wearable Personal Station) for next generation PC can define as a core terminal of 'Ubiquitous Computing' that include information processing and network function and overcome spatial limitation in acquisition of new information. As a way to acquire significant dynamic gesture data of user from haptic devices, traditional gesture recognizer based on desktop-PC using wire communication module has several restrictions such as conditionality on space, complexity between transmission mediums(cable elements), limitation of motion and incommodiousness on use. Accordingly, in this paper, in order to overcome these problems, we implement hand gesture recognition system using fuzzy algorithm and neural network for Post PC(the embedded-ubiquitous environment using blue-tooth module and WPS). Also, we propose most efficient and reasonable hand gesture recognition interface for Post PC through evaluation and analysis of performance about each gesture recognition system. The proposed gesture recognition system consists of three modules: 1) gesture input module that processes motion of dynamic hand to input data 2) Relational Database Management System(hereafter, RDBMS) module to segment significant gestures from input data and 3) 2 each different recognition modulo: fuzzy max-min and neural network recognition module to recognize significant gesture of continuous / dynamic gestures. Experimental result shows the average recognition rate of 98.8% in fuzzy min-nin module and 96.7% in neural network recognition module about significantly dynamic gestures.

A Study on Delineation of Groundwater Recharge Rate Using Water-Table Fluctuation and Unsaturate Zone Soil Water Content Model (지하수위 변동 예측 및 비포화대 함수모델을 이용한 지하수 함양율 산정 연구)

  • Cho, Jin-Wook;Park, Eun-Gyu
    • Journal of Soil and Groundwater Environment
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    • v.13 no.1
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    • pp.67-76
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    • 2008
  • In this study, a combined model of a water-table fluctuation and a soil moisture content model is proposed for the estimation of groundwater recharge rate at a given location. To evaluate the model, groundwater level data from 4 monitoring wells (Pohang Yeonil, Pohang Kibuk, Suncheon Oeseo, Hongcheon Hongcheon) of National Groundwater Monitoring Network from 1996 to 2005 and precipitation data of corresponding years are used. From the proposed methodology, the groundwater recharge rates are estimated to be from 0.5 to 61.4% for Hongcheon Hongcheon, from 1.1 to 27.4% for Pohang Yeonil, from 5.1 to 41.4% for Pohang Kibuk, and from 1.1 to 8.3% for Suncheon Oeseo. The magnitude of variation of the estimated recharge rate depends on the soil type observed near the stations. The groundwater fluctuation model used in this study includes precipitation as a unique source of water-table perturbation and there may exist corollary limitations. To improve the applicability of the proposed method, a capillary-water content constitutive model for unsaturated fractured rock media may be considered. The proposed recharge rate delineation method is physically based and uses minimum numbers of assumptions. The method may be used as a better substitute for the previous tools for delineating recharge rate of a location using water-table fluctuation method and contribute to national groundwater management plan. Further research on the spatial interpolation of the method is under progress.

An Efficient Block Segmentation and Classification Method for Document Image Analysis Using SGLDM and BP (공간의존행렬과 신경망을 이용한 문서영상의 효과적인 블록분할과 유형분류)

  • Kim, Jung-Su;Lee, Jeong-Hwan;Choe, Heung-Mun
    • The Transactions of the Korea Information Processing Society
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    • v.2 no.6
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    • pp.937-946
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    • 1995
  • We proposed and efficient block segmentation and classification method for the document analysis using SGLDM(spatial gray level dependence matrix) and BP (back Propagation) neural network. Seven texture features are extracted directly from the SGLDM of each gray-level block image, and by using the nonlinear classifier of neural network BP, we can classify document blocks into 9 categories. The proposed method classifies the equation block, the table block and the flow chart block, which are mostly composed of the characters, out of the blocks that are conventionally classified as non-character blocks. By applying Sobel operator on the gray-level document image beforebinarization, we can reduce the effect of the background noises, and by using the additional horizontal-vertical smoothing as well as the vertical-horizontal smoothing of images, we can obtain an effective block segmentation that does not lead to the segmentation into small pieces. The result of experiment shows that a document can be segmented and classified into the character blocks of large fonts, small fonts, the character recognigible candidates of tables, flow charts, equations, and the non-character blocks of photos, figures, and graphs.

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Landslide Hazard Mapping and Verification Using Probability Rainfall and Artificial Neural Networks (미래 확률강우량 및 인공신경망을 이용한 산사태 위험도 분석 기법 개발 및 검증)

  • Lee, Moung-Jin;Lee, Sa-Ro;Jeon, Seong-Woo
    • Journal of the Korean Association of Geographic Information Studies
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    • v.15 no.2
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    • pp.57-70
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    • 2012
  • The aim of this study is to analyse the landslide susceptibility and the future hazard in Inje, Korea using probability rainfalls and artificial neural network (ANN) environment based on geographic information system (GIS). Data for rainfall probability, topography, and geology were collected, processed, and compiled in a spatial database using GIS. Deokjeok-ri that had experienced 694 landslides by Typhoon Ewinia in 2006 was selected for analysis and verification. The 50% of landslide data were randomly selected to use as training data while the other 50% being used for verification. The probability of landslides for target years (1 year, 3 years, 10 years, 50 years, and 100 years) was calculated assuming that landslides are triggered by 1-day rainfall of 202 mm or 3-day cumulative rainfalls of 449 mm.